Stricter cross-compliance standards in Switzerland: Economic and environmental impacts at farm- and sector-level

A Swiss popular initiative reflecting large public concerns about the negative environmental impacts of agricultural production launched a proposal to rigorously tighten environmental cross-compliance standards. The so-called drinking water initiative (DWI) proposes restricting direct payments to farms that (1) preserve biodiversity, (2) do not use any pesticides, (3) adapt their livestock to their on-farm feed capacity and (4) do not use antibiotics regularly or prophylactically. Based on the recursive-dynamic, agent-based agricultural sector model SWISSland, we assessed, ex-ante, the impacts of the initiative on environmental and economic indicators at the farm- and sector-level. Stakeholders from both groups, supporters and opponents of the initiative, were involved in the assessment. We found that the incorporation of far more stringent environmental standards into the crosscompliance system caused a larger number of farms to opt-out: For 33-63% of the pork and poultry farms and 51-93% of the vegetable/orchards/winery farms, it was more profitable to forego direct payments. However, the majority of the ruminant farms (87%) were expected to comply with the standards. Although the non-complying farm types were associated with the most severe environmental impacts, we found that the initiative nonetheless had positive effects on water quality at the sectoral level in Switzerland: e.g., the share of pesticide-free arable land increased to 70-92%, those of the permanent cropland to 11-52%, and the nitrogen surplus decreased. However, the total agricultural production measured in calories decreased (12-21%), and therefore agricultural imports would increase. If the current direct payment budget goes completely to the complying farms, and if these farms receive a price premium, then we predict an average farm income increase of 2-34% for the complying farms; otherwise, a decrease of 6-22% will be found depending on the scenario. A sensitivity analysis showed that price uncertainties had the highest impact on farm income.